[英]How do a make sure an arbitrary number of weights sum to 1 (Python)?
I have a simulated annealing algorithm and I have a function like 我有一个模拟的退火算法,并且有一个类似的函数
result = w1*x1 + w2*x2 + ... + wn*xn
every loop of the simulated annealing when new w
values are chosen how do you make sure that the sum of w
always equal to 1 and that no individual w
value is less that 0? 选择新的w
值时,模拟退火的每个循环如何确保w
的总和始终等于1,并且每个w
值都不小于0?
Thank you very much folks! 非常感谢大家!
result = w1*x1 + w2*x2 + ... + wn*xn
you can do result = np.dot(w, x)
. 这样,您可以执行result = np.dot(w, x)
而不是result = w1*x1 + w2*x2 + ... + wn*xn
。 The condition you want on w
seems like it could come from: 您想要的w
条件似乎可能来自:
non_negative_w = np.abs(w) sum_w = np.sum(non_negative_w) normalized_non_negative_w = non_negative_w / sum_w
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